We compare two consistent estimators of the parameter vector beta of a general exponential family measurement error model with respect to their relative efficiency. The quasi score (QS) estimator uses the distribution of the regressor, the corrected score (CS) estimator does not make use of this distribution and is therefore more robust. However, if the regressor distribution is known, QS is asymptotically more efficient than CS. In some cases it is, in fact, even strictly more efficient, in the sense that the difference of the asymptotic covariance matrices of CS and QS is positive definite
We prove that the quasi-score estimator in a mean-variance model is optimal in the class of (unbiase...
We consider a regression of y on x given by a pair of mean and variance functions with a parameter v...
In a multivariate mean-variance model, the class of linear score (LS) estimators based on an unbias...
We compare two consistent estimators of the parameter vector beta of a general exponential family me...
We consider a polynomial regression model, where the covariate is measured with Gaussian errors. The...
We consider a polynomial regression model, where the covariate is measured with Gaussian errors. The...
We consider a regression of $y$ on $x$ given by a pair of mean and variance functions with a paramet...
We study a nonlinear measurement model where the response vari-able has a density belonging to the e...
The paper is a survey of recent investigations by the authors and others into the relative efficienc...
The asymptotic covariance matrices of the corrected score, the quasi score, and the simple score est...
We prove that the quasi-score estimator in a mean-variance model is optimal in the class of (unbiase...
We consider a regression of y on x given by a pair of mean and variance functions with a parameter v...
In a multivariate mean-variance model, the class of linear score (LS) estimators based on an unbias...
We compare two consistent estimators of the parameter vector beta of a general exponential family me...
We consider a polynomial regression model, where the covariate is measured with Gaussian errors. The...
We consider a polynomial regression model, where the covariate is measured with Gaussian errors. The...
We consider a regression of $y$ on $x$ given by a pair of mean and variance functions with a paramet...
We study a nonlinear measurement model where the response vari-able has a density belonging to the e...
The paper is a survey of recent investigations by the authors and others into the relative efficienc...
The asymptotic covariance matrices of the corrected score, the quasi score, and the simple score est...
We prove that the quasi-score estimator in a mean-variance model is optimal in the class of (unbiase...
We consider a regression of y on x given by a pair of mean and variance functions with a parameter v...
In a multivariate mean-variance model, the class of linear score (LS) estimators based on an unbias...